OpenRaiser/Intern-Atlas huggingface dataset:
A Distributed Demand-Side Management Framework for the Smart Grid
Venue: arXiv cs.GT 2014
Year: 2014

This paper proposes a fully distributed Demand-Side Management system for Smart Grid infrastructures, especially tailored to reduce the peak demand of residential users. In particular, we use a dynamic pricing strategy, where energy tariffs are function of the overall power demand of customers. We consider two practical cases: (1) a fully distributed approach, where each appliance decides autonomously its own scheduling, and (2) a hybrid approach, where each user must schedule all his appliances. We analyze numerically these two approaches, showing that they are characterized practically by the same performance level in all the considered grid scenarios. We model the proposed system using a non-cooperative game theoretical approach, and demonstrate that our game is a generalized ordinal potential one under general conditions. Furthermore, we propose a simple yet effective best response strategy that is proved to converge in a few steps to a pure Nash Equilibrium, thus demonstrating the robustness of the power scheduling plan obtained without any central coordination of the operator or the customers. Numerical results, obtained using real load profiles and appliance models, show that the system-wide peak absorption achieved in a completely distributed fashion can be reduced up to 55%, thus decreasing the capital expenditure (CAPEX) necessary to meet the growing energy demand.
Improved Distributed Steiner Forest Construction
Venue: arXiv cs.DC 2014
Year: 2014

We present new distributed algorithms for constructing a Steiner Forest in the CONGEST model. Our deterministic algorithm finds, for any given constant $ε>0$, a $(2+ε)$-approximation in $\tilde{O}(sk+\sqrt{\min(st,n)})$ rounds, where $s$ is the shortest path diameter, $t$ is the number of terminals, $k$ is the number of terminal components in the input, and $n$ is the number of nodes. Our randomized algorithm finds, with high probability, an $O(\log n)$- approximation in time $\tilde{O}(k+\min(s,\sqrt n)+D)$, where $D$ is the unweighted diameter of the network. We also prove a matching lower bound of $\tildeΩ(k+\min(s,\sqrt{n})+D)$ on the running time of any distributed approximation algorithm for the Steiner Forest problem. Previous algorithms were randomized, and obtained either an $O(\log n)$-approximation in $\tilde{O}(sk)$ time, or an $O(1/ε)$-approximation in $\tilde{O}((\sqrt{n}+t)^{1+ε}+D)$ time.
Analytical Modeling of Mode Selection and Power Control for Underlay D2D Communication in Cellular Networks
Venue: arXiv cs.NI 2014
Year: 2014

Device-to-device (D2D) communication enables the user equipments (UEs) located in close proximity to bypass the cellular base stations (BSs) and directly connect to each other, and thereby, offload traffic from the cellular infrastructure. D2D communication can improve spatial frequency reuse and energy efficiency in cellular networks. This paper presents a comprehensive and tractable analytical framework for D2D-enabled uplink cellular networks with a flexible mode selection scheme along with truncated channel inversion power control. Different from the existing mode selection schemes where the decision on mode selection is made based only on the D2D link distance (i.e., distance between two UEs using D2D mode of communication), the proposed mode selection scheme for a UE accounts for both the D2D link distance and cellular link distance (i.e., distance between the UE and the BS). The developed framework is used to analyze and understand how the underlaying D2D communication affects the cellular network performance. Through comprehensive numerical analysis, we investigate the expected performance gains and provide guidelines for selecting the network parameters.
Analysis of S Band Substrate Integrated Waveguide Power Divider, Circulator and Coupler
Venue: arXiv cs.ET 2014
Year: 2014

The Substrate Integrated Waveguide (SIW) technology is a very promising technique with which we can take the advantages of both waveguides and planar transmission lines. Therefore, in [2.1-3] GHz band various microwave components and devices have been designed successfully using Ansoft HFSS software. We then proceeded to the realization of the coupler and then made measurements of the frequency response in the range [2.1-3] GHz using a network analyzer. Thus, results of this modeling are presented, discussed and allow to integrate these devices in planar circuits.
Use of ARAS 360 to Facilitate Rapid Development of Articulated Total Body Biomechanical Physics Simulations
Venue: arXiv cs.OH 2014
Year: 2014

The development of 3-dimensional environments to be used within a biomechanical physics simulation framework, such as Articulated Total Body, can be laborious and time intensive. This brief article demonstrates how the ARAS 360 software package can aid the user by speeding up development time.
How and When to Flatten Java Classes?
Venue: arXiv cs.SE 2014
Year: 2014

Improving modularity and reusability are two key objectives in object-oriented programming. These objectives are achieved by applying several key concepts, such as data encapsulation and inheritance. A class in an object-oriented system is the basic unit of design. Assessing the quality of an object-oriented class may require flattening the class and representing it as it really is, including all accessible inherited class members. Thus, class flattening helps in exploring the impact of inheritance on improving code quality. This paper explains how to flatten Java classes and discusses the relationship between class flattening and some applications of interest to software practitioners, such as refactoring and indicating external quality attributes.
Electronic Health Records: Cure-all or Chronic Condition?
Venue: arXiv cs.CY 2014
Year: 2014

Computer-based information systems feature in almost every aspect of our lives, and yet most of us receive handwritten prescriptions when we visit our doctors and rely on paper-based medical records in our healthcare. Although electronic health record (EHR) systems have long been promoted as a cost-effective and efficient alternative to this situation, clear-cut evidence of their success has not been forthcoming. An examination of some of the underlying problems that prevent EHR systems from delivering the benefits that their proponents tout identifies four broad objectives - reducing cost, reducing errors, improving coordination and improving adherence to standards - and shows that they are not always met. The three possible causes for this failure to deliver involve problems with the codification of knowledge, group and tacit knowledge, and coordination and communication. There is, however, reason to be optimistic that EHR systems can fulfil a healthy part, if not all, of their potential.
Band Limited Signals Observed Over Finite Spatial and Temporal Windows: An Upper Bound to Signal Degrees of Freedom
Venue: arXiv cs.IT 2014
Year: 2014

The study of degrees of freedom of signals observed within spatially diverse broadband multipath fields is an area of ongoing investigation and has a wide range of applications, including characterising broadband MIMO and cooperative networks. However, a fundamental question arises: given a size limitation on the observation region, what is the upper bound on the degrees of freedom of signals observed within a broadband multipath field over a finite time window? In order to address this question, we characterize the multipath field as a sum of a finite number of orthogonal waveforms or spatial modes. We show that (i) the "effective observation time" is independent of spatial modes and different from actual observation time, (ii) in wideband transmission regimes, the "effective bandwidth" is spatial mode dependent and varies from the given frequency bandwidth. These findings clearly indicate the strong coupling between space and time as well as space and frequency in spatially diverse wideband multipath fields. As a result, signal degrees of freedom does not agree with the well-established degrees of freedom result as a product of spatial degrees of freedom and time-frequency degrees of freedom. Instead, analogous to Shannon's communication model where signals are encoded in only one spatial mode, the available signal degrees of freedom in spatially diverse wideband multipath fields is the time-bandwidth product result extended from one spatial mode to finite modes. We also show that the degrees of freedom is affected by the acceptable signal to noise ratio (SNR) in each spatial mode.
An Overview of Face Liveness Detection
Venue: arXiv cs.CV 2014
Year: 2014

Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach.
Graph Regularized Non-negative Matrix Factorization By Maximizing Correntropy
Venue: arXiv cs.CV 2014
Year: 2014

Non-negative matrix factorization (NMF) has proved effective in many clustering and classification tasks. The classic ways to measure the errors between the original and the reconstructed matrix are $l_2$ distance or Kullback-Leibler (KL) divergence. However, nonlinear cases are not properly handled when we use these error measures. As a consequence, alternative measures based on nonlinear kernels, such as correntropy, are proposed. However, the current correntropy-based NMF only targets on the low-level features without considering the intrinsic geometrical distribution of data. In this paper, we propose a new NMF algorithm that preserves local invariance by adding graph regularization into the process of max-correntropy-based matrix factorization. Meanwhile, each feature can learn corresponding kernel from the data. The experiment results of Caltech101 and Caltech256 show the benefits of such combination against other NMF algorithms for the unsupervised image clustering.
On Analysis and Generation of some Biologically Important Boolean Functions
Venue: arXiv cs.SY 2014
Year: 2014

Boolean networks are used to model biological networks such as gene regulatory networks. Often Boolean networks show very chaotic behaviour which is sensitive to any small perturbations. In order to reduce the chaotic behaviour and to attain stability in the gene regulatory network, nested Canalizing Functions (NCFs) are best suited. NCFs and its variants have a wide range of applications in systems biology. Previously, many works were done on the application of canalizing functions, but there were fewer methods to check if any arbitrary Boolean function is canalizing or not. In this paper, by using Karnaugh Map this problem is solved and also it has been shown that when the canalizing functions of variable is given, all the canalizing functions of variable could be generated by the method of concatenation. In this paper we have uniquely identified the number of NCFs having a particular Hamming Distance (H.D) generated by each variable as starting canalizing input. Partially NCFs of 4 variables has also been studied in this paper.
Complexity of Higher-Degree Orthogonal Graph Embedding in the Kandinsky Model
Venue: arXiv cs.CG 2014
Year: 2014

We show that finding orthogonal grid-embeddings of plane graphs (planar with fixed combinatorial embedding) with the minimum number of bends in the so-called Kandinsky model (which allows vertices of degree $> 4$) is NP-complete, thus solving a long-standing open problem. On the positive side, we give an efficient algorithm for several restricted variants, such as graphs of bounded branch width and a subexponential exact algorithm for general plane graphs.
A Proof Theoretic Study of Soft Concurrent Constraint Programming
Venue: arXiv cs.LO 2014
Year: 2014

Concurrent Constraint Programming (CCP) is a simple and powerful model for concurrency where agents interact by telling and asking constraints. Since their inception, CCP-languages have been designed for having a strong connection to logic. In fact, the underlying constraint system can be built from a suitable fragment of intuitionistic (linear) logic --ILL-- and processes can be interpreted as formulas in ILL. Constraints as ILL formulas fail to represent accurately situations where "preferences" (called soft constraints) such as probabilities, uncertainty or fuzziness are present. In order to circumvent this problem, c-semirings have been proposed as algebraic structures for defining constraint systems where agents are allowed to tell and ask soft constraints. Nevertheless, in this case, the tight connection to logic and proof theory is lost. In this work, we give a proof theoretical interpretation to soft constraints: they can be defined as formulas in a suitable fragment of ILL with subexponentials (SELL) where subexponentials, ordered in a c-semiring structure, are interpreted as preferences. We hence achieve two goals: (1) obtain a CCP language where agents can tell and ask soft constraints and (2) prove that the language in (1) has a strong connection with logic. Hence we keep a declarative reading of processes as formulas while providing a logical framework for soft-CCP based systems. An interesting side effect of (1) is that one is also able to handle probabilities (and other modalities) in SELL, by restricting the use of the promotion rule for non-idempotent c-semirings.This finer way of controlling subexponentials allows for considering more interesting spaces and restrictions, and it opens the possibility of specifying more challenging computational systems.
A Methodology for Information Flow Experiments
Venue: arXiv cs.CR 2014
Year: 2014

Information flow analysis has largely ignored the setting where the analyst has neither control over nor a complete model of the analyzed system. We formalize such limited information flow analyses and study an instance of it: detecting the usage of data by websites. We prove that these problems are ones of causal inference. Leveraging this connection, we push beyond traditional information flow analysis to provide a systematic methodology based on experimental science and statistical analysis. Our methodology allows us to systematize prior works in the area viewing them as instances of a general approach. Our systematic study leads to practical advice for improving work on detecting data usage, a previously unformalized area. We illustrate these concepts with a series of experiments collecting data on the use of information by websites, which we statistically analyze.
Transmission Rank Selection for Opportunistic Beamforming with Quality of Service Constraints
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we consider a multi-cell multi-user MISO broadcast channel. The system operates according to the opportunistic beamforming framework in a multi-cell environment with variable number of transmit beams (may alternatively be referred as the transmission rank) at each base station. The maximum number of co-scheduled users in a cell is equal to its transmission rank, thus increasing it will have the effect of increasing the multiplexing gain. However, this will simultaneously increase the amount of interference in the network, which will decrease the rate of communication. This paper focuses on optimally setting the transmission rank at each base station such that a set of Quality of Service (QoS) constraints, that will ensure a guaranteed minimum rate per beam at each base station, is not violated. Expressions representing the achievable region of transmission ranks are obtained considering different network settings. The achievable transmission rank region consists of all achievable transmission rank tuples that satisfy the QoS constraints. Numerical results are also presented to provide further insights on the feasibility problem.
Optimal Learners for Multiclass Problems
Venue: arXiv cs.LG 2014
Year: 2014

The fundamental theorem of statistical learning states that for binary classification problems, any Empirical Risk Minimization (ERM) learning rule has close to optimal sample complexity. In this paper we seek for a generic optimal learner for multiclass prediction. We start by proving a surprising result: a generic optimal multiclass learner must be improper, namely, it must have the ability to output hypotheses which do not belong to the hypothesis class, even though it knows that all the labels are generated by some hypothesis from the class. In particular, no ERM learner is optimal. This brings back the fundmamental question of "how to learn"? We give a complete answer to this question by giving a new analysis of the one-inclusion multiclass learner of Rubinstein et al (2006) showing that its sample complexity is essentially optimal. Then, we turn to study the popular hypothesis class of generalized linear classifiers. We derive optimal learners that, unlike the one-inclusion algorithm, are computationally efficient. Furthermore, we show that the sample complexity of these learners is better than the sample complexity of the ERM rule, thus settling in negative an open question due to Collins (2005).
Truthful Learning Mechanisms for Multi-Slot Sponsored Search Auctions with Externalities
Venue: arXiv cs.GT 2014
Year: 2014

Sponsored search auctions constitute one of the most successful applications of microeconomic mechanisms. In mechanism design, auctions are usually designed to incentivize advertisers to bid their truthful valuations and to assure both the advertisers and the auctioneer a non-negative utility. Nonetheless, in sponsored search auctions, the click-through-rates (CTRs) of the advertisers are often unknown to the auctioneer and thus standard truthful mechanisms cannot be directly applied and must be paired with an effective learning algorithm for the estimation of the CTRs. This introduces the critical problem of designing a learning mechanism able to estimate the CTRs at the same time as implementing a truthful mechanism with a revenue loss as small as possible compared to an optimal mechanism designed with the true CTRs. Previous work showed that, when dominant-strategy truthfulness is adopted, in single-slot auctions the problem can be solved using suitable exploration-exploitation mechanisms able to achieve a per-step regret (over the auctioneer's revenue) of order $O(T^{-1/3})$ (where T is the number of times the auction is repeated). It is also known that, when truthfulness in expectation is adopted, a per-step regret (over the social welfare) of order $O(T^{-1/2})$ can be obtained. In this paper we extend the results known in the literature to the case of multi-slot auctions. In this case, a model of the user is needed to characterize how the advertisers' valuations change over the slots. We adopt the cascade model that is the most famous model in the literature for sponsored search auctions. We prove a number of novel upper bounds and lower bounds both on the auctioneer's revenue loss and social welfare w.r.t. to the VCG auction and we report numerical simulations investigating the accuracy of the bounds in predicting the dependency of the regret on the auction parameters.
Performance Provisioning and Energy Efficiency in Cloud and Distributed Computing Systems
Venue: arXiv cs.DC 2014
Year: 2014

In recent years, the issue of energy consumption in high performance computing (HPC) systems has attracted a great deal of attention. In response to this, many energy-aware algorithms have been developed in different layers of HPC systems, including the hardware layer, service layer and system layer. These algorithms are of two types: first, algorithms which directly try to improve the energy by tweaking frequency operation or scheduling algorithms; and second, algorithms which focus on improving the performance of the system, with the assumption that efficient running of a system may indirectly save more energy. In this thesis, we develop algorithms in both layers. First, we introduce three algorithms to directly improve the energy of scheduled tasks at the hardware level by using Dynamic Voltage Frequency Scaling (DVFS). Second, we propose two algorithms for modelling and resource provisioning of MapReduce applications (a well-known parametric distributed framework currently used by Google, Yahoo, Facebook and LinkedIn) based on its configuration parameters. Certainly, estimating the performance (e.g., execution time or CPU clock ticks) of a MapReduce application can be later used for smart scheduling of such applications in clouds or clusters. To evaluate the algorithms, we have conducted extensive simulation and real experiments on a 5-node physical cluster with up to 25 virtual nodes, using both synthetic and real world applications. Also, the proposed new algorithms are compared with existing algorithms by experimentation, and the experimental results reveal new information on the performance of these algorithms, as well as on the properties of MapReduce and DVFS. In the end, three open problems are revealed by the experimental observations, and their importance is explained.
Spatial Coupling of Generator Matrix: A General Approach to Design of Good Codes at a Target BER
Venue: arXiv cs.IT 2014
Year: 2014

For any given short code (referred to as the basic code), block Markov superposition transmission (BMST) provides a simple way to obtain predictable extra coding gain by spatial coupling the generator matrix of the basic code. This paper presents a systematic design methodology for BMST systems to approach the channel capacity at any given target bit-error-rate (BER) of interest. To simplify the design, we choose the basic code as the Cartesian product of a short block code. The encoding memory is then inferred from the genie-aided lower bound according to the performance gap of the short block code to the corresponding Shannon limit at the target BER. In addition to the sliding-window decoding algorithm, we propose to perform one more phase decoding to remove residual (rare) errors. A new technique that assumes a noisy genie is proposed to upper bound the performance. Under some mild assumptions, these genie-aided bounds can be used to predict the performance of the proposed two-phase decoding algorithm in the extremely low BER region. Using the Cartesian product of a repetition code as the basic code, we construct a BMST system with an encoding memory 30 whose performance at the BER of $10^{-15}$ can be predicted within one dB away from the Shannon limit over the binary-input additive white Gaussian noise channel (BI-AWGNC).
A Review of Image Mosaicing Techniques
Venue: arXiv cs.CV 2014
Year: 2014

Image Mosaicing is a method of constructing multiple images of the same scene into a larger image. The output of the image mosaic will be the union of two input images. Image-mosaicing algorithms are used to get mosaiced image. Image Mosaicing processed is basically divided in to 5 phases. Which includes; Feature point extraction, Image registration, Homography computation, Warping and Blending if Image. Various corner detection algorithm is being used for Feature extraction. This corner produces an efficient and informative output mosaiced image. Image mosaicing is widely used in creating 3D images, medical imaging, computer vision, data from satellites, and military automatic target recognition.